A Scalable Safety Critical Control Framework for Nonlinear Systems

A Scalable Safety Critical Control Framework for Nonlinear Systems
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非线性系统的可扩展安全关键控制框架

DOI:
10.1109/access.2020.3025248
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发表时间:
2020
期刊:
影响因子:
3.9
通讯作者:
Ames, Aaron D.
Ames, Aaron D.
中科院分区:
计算机科学3区
文献类型:
--
作者:
Gurriet, Thomas;Mote, Mark;Singletary, Andrew;Nilsson, Petter;Feron, Eric;Ames, Aaron D.

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安全关键控制有两种主要方法。第一个依赖于控制不变集的计算,并在本工作的第一部分中提出。第二种方法源自最优控制主题,并依赖于在线实现模型预测控制器的能力来保证系统的安全。在第二种方法中,通过针对状态和控制输入的一些明确定义的约束来解决控制问题主题,从而在规划阶段确保安全。两种方法都有明显的优点,但也有阻碍其实际有效性的主要缺点,即第一种方法的可扩展性和第二种方法的计算复杂性。因此,我们提出了一种方法,该方法借鉴了这两种方法的优点,以提供有效且可扩展的方法来确保非线性动力系统的安全性。特别是,我们表明,确定稳定系统的备用控制律实际上足以利用本工作第一部分中提出的一些集合不变性条件。事实上,人们只需要能够在这一备份定律下对有限范围内的系统闭环动力学进行数值积分,即可计算评估监管图和加强安全性所需的所有信息。还研究了放宽备用法稳定性要求的效果,并提出了较弱但更实用的安全保障。然后,我们探讨备份法则的最优性与最终安全过滤器的保守程度之间的关系。最后,提出了在保守性和计算复杂性之间进行不同程度的权衡来选择安全输入的方法,并在多个机器人系统上进行了说明,即:两轮倒立摆(Segway)、工业机械手、四旋翼飞行器和下半身外骨骼。
There are two main approaches to safety-critical control. The first one relies on computation of control invariant sets and is presented in the first part of this work. The second approach draws from the topic of optimal control and relies on the ability to realize Model-Predictive-Controllers online to guarantee the safety of a system. In the second approach, safety is ensured at a planning stage by solving the control problem subject for some explicitly defined constraints on the state and control input. Both approaches have distinct advantages but also major drawbacks that hinder their practical effectiveness, namely scalability for the first one and computational complexity for the second. We therefore present an approach that draws from the advantages of both approaches to deliver efficient and scalable methods of ensuring safety for nonlinear dynamical systems. In particular, we show that identifying a backup control law that stabilizes the system is in fact sufficient to exploit some of the set-invariance conditions presented in the first part of this work. Indeed, one only needs to be able to numerically integrate the closed-loop dynamics of the system over a finite horizon under this backup law to compute all the information necessary for evaluating the regulation map and enforcing safety. The effect of relaxing the stabilization requirements of the backup law is also studied, and weaker but more practical safety guarantees are brought forward. We then explore the relationship between the optimality of the backup law and how conservative the resulting safety filter is. Finally, methods of selecting a safe input with varying levels of trade-off between conservatism and computational complexity are proposed and illustrated on multiple robotic systems, namely: a two-wheeled inverted pendulum (Segway), an industrial manipulator, a quadrotor, and a lower body exoskeleton.
主动集不变性的在线方法
DOI: --
发表时间: 2018
期刊: IEEE Conference on Decision and Control
影响因子: --
作者:
Thomas Gurriet;Mark L. Mote;A. Ames;E. Feron
通讯作者: E. Feron
DOI: --
发表时间: 2015
期刊: SNR@CAV
影响因子: --
作者:
Ian M. Mitchell
通讯作者: Ian M. Mitchell
DOI: --
发表时间: 2019
期刊: IEEE/SICE International Symposium on System Integration
影响因子: --
作者:
Justin Carpentier;Guilhem Saurel;Gabriele Buondonno;Joseph Mirabel;F. Lamiraux;O. Stasse;N. Mansard
通讯作者: N. Mansard
DOI: 10.1016/0734-189x(89)90038-8
发表时间: 1989-06
期刊: Comput. Vis. Graph. Image Process.
影响因子: --
作者:
H. Samet
通讯作者: H. Samet
DOI: 10.1007/s10514-012-9321-0
发表时间: 2013-04-01
期刊: AUTONOMOUS ROBOTS
影响因子: 3.5
作者:
Hornung, Armin;Wurm, Kai M.;Burgard, Wolfram
通讯作者: Burgard, Wolfram